Project Summary Cold Spring Harbor Laboratory (CSHL) is a private, not-for-profit institution dedicated to research and education in biology, with leading research programs in genomics, neuroscience, quantitative biology, plant biology, and cancer. Many activities at CSHL depend critically on high-performance computing resources, but at present, investigators have limited access to Graphics Processing Units (GPUs) and large-memory compute nodes. This deficiency is beginning to hamper a wide variety of biomedical research activities, particularly in the key areas of genomics, neuroscience and structural biology, where such specialty hardware is becoming essential for many important computational analyses. Here, we propose to acquire four state-of-the-art GPU nodes, each equipped with eight Nvidia Tesla V100, SXM2, 32GB GPUs, two 20-core 2.5 GHz Intel Xeon-Gold 6248 (Cascade Lake) processors, and 768 GB of RAM. A second-generation Nvidia NVLink will provide for 300 GB/s inter-GPU communication. In addition, we propose to acquire one large-memory node with 3 TB of RAM and four 20-core 2.5 GHz Intel Xeon-Gold 6248 (Cascade Lake) processors, as well as a top-of-rack 10 Gb Ethernet switch to interconnect the servers with each other and with our existing computer cluster. These new resources will enable a wide variety of innovative research across fields, with direct implications for human health. In genomics, applications will include RNA-seq read mapping; alignment, base-calling, and genome assembly for long-read sequence data; clustering of single cell RNA-seq data; analysis of transposable elements; deep-learning methods for prediction of the fitness consequences of mutations; and deep-learning methods for interpreting high-throughput mutagenesis experiments. In neuroscience, they will include analysis of multi-neuron activity recordings; analysis of mouse brain images; and artificial neural network models of the human olfactory system, of audio features, and of behavior as a function of changing motivations. In structural biology, they will include image processing and 3D reconstruction from cryo-electron microscopy data. These new compute nodes will have a primary impact on the research programs of nine major users from the CSHL faculty with substantial NIH funding. They will also impact three minor users. The new GPU and large-memory nodes will be fully integrated with a soon-to-be-upgraded high-performance computer cluster and managed by the experienced Information Technology group at CSHL, with oversight from a committee of seven faculty members and two IT staff members. Altogether, these new computational resources will substantially enhance the overall computational infrastructure at CSHL.